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  2. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    Segmentation of a 512 × 512 image takes less than a second on a modern (2015) GPU using the U-Net architecture. [1] [3] [4] [5] The U-Net architecture has also been employed in diffusion models for iterative image denoising. [6] This technology underlies many modern image generation models, such as DALL-E, Midjourney, and Stable Diffusion.

  3. Statistical region merging - Wikipedia

    en.wikipedia.org/wiki/Statistical_Region_Merging

    A major use of SRM is in image processing where higher number color palettes in an image are converted into lower number palettes by merging the similar colors' palettes together. The merging criteria include allowed color ranges, minimum size of a region, maximum size of a region, allowed number of platelets, etc.

  4. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    The images have been rigorously collected during oceanic explorations and human-robot collaborative experiments, and annotated by human participants. Images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates), aquatic plants, wrecks/ruins, human divers, robots, and sea-floor. 1,635 Images Segmentation 2020

  5. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...

  6. Category:Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Category:Image_segmentation

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  7. Insight Segmentation and Registration Toolkit - Wikipedia

    en.wikipedia.org/wiki/Insight_Segmentation_and...

    In addition, an automated wrapping process generates interfaces between C++ and other programming languages such as Java and Python. This enables developers to create software using a variety of programming languages. ITK's implementation employs the technique of generic programming through the use of C++ templates.

  8. Graph cuts in computer vision - Wikipedia

    en.wikipedia.org/wiki/Graph_cuts_in_computer_vision

    As applied in the field of computer vision, graph cut optimization can be employed to efficiently solve a wide variety of low-level computer vision problems (early vision [1]), such as image smoothing, the stereo correspondence problem, image segmentation, object co-segmentation, and many other computer vision problems that can be formulated in terms of energy minimization.

  9. ImageJ - Wikipedia

    en.wikipedia.org/wiki/ImageJ

    Custom acquisition, analysis and processing plugins can be developed using ImageJ's built-in editor and a Java compiler. User-written plugins make it possible to solve many image processing and analysis problems, from three-dimensional live-cell imaging [ 6 ] to radiological image processing, [ 7 ] multiple imaging system data comparisons [ 8 ...